SUMMARY: This project involves the application of digital computer technology to the diagnosis of disease based on the microscopic morphology of stained tissue sections. Techniques of digital image processing are applied to delineate nuclei in digital images of human urinary bladder epithelium and to compute mathematical characterizations of various morphologic attributes such as size, shape, texture and tissue architecture. Techniques of statistical decision theory and cluster analysis are applied to the problem of objectively characterizing tissue sections and devising classification and grading systems for them based exclusively on quantitative morphometry and biochemical composition.